Decentralized marriage models

Most matching algorithms are centralized in that a single agent determines how other agents are matched together. This is contrary to how humans form matches in the real world. We propose three decentralized approaches for finding matchings that are inspired by three techniques that humans use to find matches: a grid environment, with agents wandering around, interacting and deciding preferences over potential partners; affiliation networks where agencies recommend potential partners; and small-world social networks, where individuals are probabilistically introduced to one another by friends. We introduce a heuristic algorithm that can be used in each of these environments. We also explore how this algorithm can scale to a large number of agents.